University of Texas at Arlington

About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.

Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities

Abstract: With the deployment of advanced metering infrastructure (AMI), an avalanche of new energy-use information became available. Better understanding of the actual power consumption patterns of customers is critical for improving load forecasting and efficient deployment of smart grid technologies to enhance operation, energy management, and planning of electric power systems. Unlike traditional aggregated system-level load forecasting, the AMI data introduces a fresh perspective to the way load forecasting is performed, ranging from very short-term load forecasting to long-term load forecasting at the system level, regional level, feeder level, or even down to the consumer level. This paper addresses the efforts involved in improving the system level intraday load forecasting by applying clustering to identify groups of customers with similar load consumption patterns from smart meters prior to performing load forecasting.

Transposase-Derived Transcription Factors Regulate Light Signaling in Arabidopsis

Abstract: Plants use light as a major source of information for optimizing growth and development. The photoreceptor phytochrome A (phyA) mediates various far-red light induced responses. Here, we show that Arabidopsis FHY3 and FAR1, which encode two proteins related to Mutator-like transposases, act together to modulate phyA signaling by directly activating the transcription of FHY1 and FHL, whose products are essential for light-induced phyA nuclear accumulation and subsequent light responses. FHY3 and FAR1 possess separable DNA-binding and transcriptional activation domains that are highly conserved in Mutator-like transposases. Further, expression of FHY3 and FAR1 is negatively regulated by phyA signaling. We propose that FHY3 and FAR1 define a novel class of transcription factors co-opted from an ancient Mutator-like transposase(s) to modulate phyA signaling homeostasis in higher plants.